Spec Driven Development
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
作者提供的说明(英文原文)
Measure MCP servers, pin the approved tool surface, refuse calls to tools that changed. Local-first.
这三项永远不会合并成一个分数:意见、测量和人气是不同的东西。
我们还没有为它写通俗的介绍。下面是我们从注册中心读取到的事实。
选择你使用的 AI 应用,然后复制设置。
你需要
你用的是哪个应用?
在上方选择你的应用。我们会记住它,下次按钮会显示“安装到 …”。
打开 Claude Desktop → Settings → Developer → Edit Config,把下面的内容粘贴到 claude_desktop_config.json
{
"mcpServers": {
"mcpgawk": {
"command": "uvx",
"args": [
"mcpgawk",
"mcp"
]
}
}
}在终端中运行这条命令
claude mcp add mcpgawk -- uvx mcpgawk mcp粘贴到项目中的 .cursor/mcp.json,或 ~/.cursor/mcp.json
{
"mcpServers": {
"mcpgawk": {
"command": "uvx",
"args": [
"mcpgawk",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
粘贴到项目中的 .vscode/mcp.json
{
"servers": {
"mcpgawk": {
"type": "stdio",
"command": "uvx",
"args": [
"mcpgawk",
"mcp"
]
}
}
}浏览器会先询问是否打开应用,然后应用会显示设置并请你确认。密钥的值会留空,由你自己填写。
这个服务器在你的电脑上运行,而 ChatGPT 只能连接互联网上的服务器。请选择其他应用。
你的选择通过 Cookie 保存在这台设备上,无需账户。
这些设置是根据作者在注册中心的条目生成的。如果 README 的写法不同,请以 README 为准。
它在你的电脑上运行;安装后,工具列表会显示在你的 AI 应用中。
我们检查的是任何人都能看到的信息;我们没有阅读代码。不适用的检查项不计入总数。 · 检查于 2026年11月7日
注册名称已通过 GitHub 账户 gawk-dev 验证,该账户拥有此仓库
我们还没有从 GitHub 读取这个仓库
我们还没有从 GitHub 读取这个仓库
它在你的电脑上运行,没有互联网端点
在你的电脑上运行,改用本地设置
它在你的电脑上运行;我们只能读取互联网端点的工具列表
与注册中心里这个分类中所有活跃的服务器比较。只有当发布者拥有该仓库时,星标数才计入。
它在 1 项适用的基础检查中通过了 1 项。我们没有阅读代码。在添加密钥或令牌之前,请先看看这个服务器要求哪些权限,并使用只具备所需权限的密钥。
注册中心没有列出必需的密钥,不过有些服务器会在首次使用时要求你登录。
它在你的电脑上运行。你的 AI 应用会在需要时启动它,数据不会经过作者的服务器(除非它自己调用在线服务)。
GitHub 仓库最后更新于–,最新版本(0.1.83)于前天进入注册中心。
支持 MCP 的应用,例如 Claude Desktop、Claude Code、Cursor 和 VS Code。你的电脑上还需要有 Python (uv)。
同一分类中有:Spec Driven Development, Remote Desktop Commander, Tools MCP
同一分类中其他作者的服务器,按星标数排序。
如何看卡片:★ GitHub 星标i三大支柱:评价 · 检查 · 使用情况i更新 = 最新版本发布到注册中心的时间i
MCP Server that facilitates spec-driven development workflows, not just Vibe Coding.
Remote Desktop Commander: use files, terminal and processes on your own computers from any AI app.
Web production tools for AI agents: contrast, JP text, WebP, JSON-LD, slugs, dates and 40+ more
按原文从作者的仓库复制。PopNx MCP 没有审查或背书其内容。HTML、图片和脚本已被移除。链接会离开本站。
One gateway in the path. On your machine.
Featured on Product Hunt.
Your agents call Model Context Protocol servers that can change what their tools do *after* you approved them, and the agent will call the new one without noticing. mcpgawk reads every server your agents can reach, checks every call against a baseline you approved, and blocks the ones that changed. It runs on your machine and uploads nothing.
The same engine powers mcpgawk Platform: mcpgawk enforce puts one endpoint in front of the whole fleet with a key per caller, policy on every call and a hash-chained audit log, and mcpgawk monitor watches the servers you approved around the clock and tells you when one drifts. This free layer is the seeing and the blocking underneath it. mcpgawk Platform is one subscription per person for up to 3 machines: start a free 7-day trial at https://mcp.gawk.dev/trial.html?utm_source=github&utm_medium=readme (no card) or subscribe at https://mcp.gawk.dev/subscribe. Then mcpgawk login on this same install fetches the paid engine and turns those on — one more command, nothing else to set up.
Watch: mcpgawk in 64 seconds. A tool you approved changes in an update; mcpgawk refuses the call until you decide.
mcpgawk demo — its own output, in a sandbox that touches nothing of yours. Run the same command and you get the same thing.
A server you approved can change what its tools do afterwards. Nothing in MCP tells your agent that happened — it just calls the new tool. That is the rug-pull, and it is the case mcpgawk is built for.
Two things follow from being able to see a server properly. You find out what each one can reach before you trust it, and you find out what it costs: every tool is loaded into your context on every request, used or not.
mcpgawk guard installs one pre-execution hook and a tool that appeared after you approved the server does not run.mcpgawk verify drives tools in a sandbox and reports what they actually did — exfiltration, SSRF, poisoning — reproduced before it is reported.mcpgawk guard install puts one pre-execution hook in your agent's loop. The decision is local, in about 10ms, with nothing to sign in to. Works on 6 of the 21 supported clients; the rest have no hook point and are named, not glossed over.mcpgawk verify drives tools in a sandbox and reports what they did: exfiltration, SSRF, tool poisoning, secret leaks. The sandbox is a proxy by default, so it needs no Docker; Docker adds full container isolation when you have it. Safe mode drives only provably read-only tools, and every tool it skips is named as skipped.mcpgawk decide opens a local screen for what changed. The buttons live on the tokened link printed in your terminal, so an agent that opened the page cannot approve its own way past a block.mcpgawk panel: every server, every decision, every piece of evidence.mcpgawk changes shows every change to a server's tool surface between the snapshots you have recorded: tools added or removed, input schemas widened, descriptions and annotations rewritten. It reads your local history, so it works for a server you approved weeks ago — the one thing a fresh scan can never tell you.mcp-remote bridge).--track).--supply-chain and --oauth-scopes.CLI (any terminal):
uv tool install --force mcpgawk # or: pipx install --force mcpgawk
mcpgawk # finds every agent config on the machine itself
Run it as an MCP server: mcpgawk mcp (stdio), or uvx mcpgawk mcp.
Editor (VS Code / Cursor): install mcpgawk from the VS Code Marketplace or Open VSX. It scans your workspace mcp.json and shows cost + capability flags inline. The extension drives this engine as a subprocess — it is built and released separately, so its source is not in this repository.
CI (GitHub Action): gate every PR on token budget / drift (Marketplace):
- uses: gawk-dev/mcpgawk@v1
with: { config: mcp.json, max-tokens: 8000, fail-on-flagged: true }
mcpgawk guard install. After that a tool that appears on a server you already approved does not get called.mcpgawk # first run: every agent config on this machine
mcpgawk demo # the whole arc in a sandbox — approve, drift, block mcpgawk guard install # put the baseline in your agent's loop mcpgawk guard status # is protection actually on? mcpgawk decide # what changed, and approve it as a human mcpgawk panel # the local page: servers, decisions, evidence mcpgawk verify mcp.json # run the servers and watch what they do mcpgawk changes # what changed on your servers since you approved them mcpgawk login # licence? one command fetches the paid engine (enforce, monitor)
Scanning on its own, if that is all you want:
mcpgawk scan mcp.json # a whole config
mcpgawk scan --stdio "npx -y @modelcontextprotocol/server-filesystem@2026.8.31 /tmp" mcpgawk scan --http https://host/mcp --header "Authorization: Bearer $TOKEN" mcpgawk scan --sse https://host/sse mcpgawk scan mcp.json --track # record + detect rug-pulls over time mcpgawk scan mcp.json --json # machine-readable labels mcpgawk scan mcp.json --verbose # full per-tool table, not just flagged tools mcpgawk scan mcp.json --supply-chain # opt-in: npm/PyPI deprecation check (network) mcpgawk scan mcp.json --oauth-scopes # opt-in: decode a supplied Bearer JWT's scope
Keep tokens out of the config file. Under mcpgawk wrap, an env value written as keychain: (or keychain: @ ) is read from your macOS Keychain when the server starts and placed in the server's environment only. The config holds a reference, the agent sees a reference, mcpgawk stores nothing. A reference that cannot be read refuses to start the server and names the reference, never a value.
"github": { "command": "mcpgawk", "args": ["wrap", "--", "npx", "-y", "@modelcontextprotocol/server-github"],
"env": { "GITHUB_PERSONAL_ACCESS_TOKEN": "keychain:gh-work" } }
--verbose for the full per-tool table).--track turns it into rug-pull detection over time.只显示了开头部分;其余内容请在仓库中阅读